Spectral characteristics of plant communities from salt marshes:A case study from Chongming Dongtan,Yangtzeestuary,China

The spectral reflectance of recently formed salt marshes at the mouth of the Yangtze River, which are undergoing invasion by Spartina alterniflora, were assessed to determine the potential utility of remotely sensed data in assessing future invasion and changes in species composition. Following a review of published research on remote sensing of salt marshes, 53 locations along three transects were sampled for paired data on plant species composition and spectral reflectance using a FieldSpec™ Pro JR Field Portable Spectroradiometer. Spectral data were processed concerning reflectance, and the averaged reflectance values for each sample were reanalysed to correspond to a 12-waveband bandset of the Compact Airborne Spectral Imager. The spectral data were summarised using principal components analysis (PCA) and the relationships between the vegetation composition, and the PCA axes of spectral data were examined. The first PCA axis of the reflectance data showed a strong correlation with variability in near infrared reflectance and ‘brightness’, while the second axis was correlated with visible reflectance and ‘greenness’. Total vegetation cover, vegetation height, and mudflat cover were all significantly related to the first axis. The implications of this in terms of the ability of remote sensing to distinguish the various salt marsh species and in particular the invasive species S. alterniflora were discussed. Major differences in species with various physiognomies could be recognised but problems occurred in separating early colonising S. alterniflora from other species at that stage. Further work using multi-seasonal hyperspectral data might assist in solving these problems.     

林(竹)草不同植被恢复模式下的土壤物理特性

利用建立生态定位观测场,对华西雨屏区洪雅县低山区退耕还林中的桦木+扁穗牛鞭草、苦竹+扁穗牛鞭草、纯扁穗牛鞭草和撑绿杂交竹＋扁穗牛鞭草4种林（竹）草植被类型进行定位观测,研究不同植被恢复类型对土壤物理特性的改良。试验结果表明：林（竹）草不同植被类型植被恢复5年后,土壤0～40 cm土层的砂粒和粗粉粒百分含量均有一定的下降,在一定程度上逆转了原坡耕地土壤继续“粗化”的趋势;4种植被恢复类型土壤0～40 cm土层的物理性粘粒含量与农耕地相比均有一定提高,在一定程度上增强了固持土壤养分的能力,以苦竹＋扁穗牛鞭草改良效果最好;与农耕地相比,4种植被恢复类型土壤0～40 cm土层土壤容重有增有减,以苦竹＋扁穗牛鞭草和撑绿杂交竹＋扁穗牛鞭草植被恢复类型改良效果相对较优;虽然除纯牛鞭草地外其它3种植被恢复类型土壤0～40 cm的总孔隙度与农耕地相比都有一定程度的增加,但土壤总孔隙度都偏小,非毛管孔隙/毛管孔隙值也不合理。可见土壤结构的改良并非退耕后植被恢复短期内就能实现的,还需长时间的植被保护、合理的经营。〖     

Identification of Forest Vegetation Using Vegetation Indices

Abstract

Spectral feature of forest vegetation with remote sensing techniques is the research topic all over the world, because forest plays an important role in human beings' living environment. Research on vegetation classification with vegetation index is still very little recently. This paper proposes a method of identifying forest types based on vegetation indices, because the contrast of absorbing red waveband with reflecting near-infrared waveband strongly for different vegetation types is recognized as the theoretic basis of vegetation analysis with remote sensing. Vegetation index is highly related to leaf area index, absorbed photosynthetically active radiation and vegetation cover. Vegetation index reflects photosynthesis intensity of plants and manifests different forest types. According to reflectance data of forest canopy and soil line equation NIR=1.506R+0.0076 in Jingyuetan, Changchun of China, many vegetation indices are calculated and analyzed. The result shows that the relationships between vegetation indices and forest types are that perpendicular vegetation index (PVI) identifies broadleaf forest and coniferous forest the most easily; the next is transformed soil-adjusted vegetation index (TSVI) and modified soil-adjusted vegetation index (MSVI), but their calculation is complex. Ratio vegetation index (RVI) values of different coniferous forest vary obviously, so RVI can classify conifers. Therefore, the combination of PVI and RVI is evaluated to classify different vegetation types.     

Assessing conservation opportunity on private land: socio-economic, behavioral, and spatial dimensions

This study presents a method for assessing conservation opportunity on private land based on landholders' socio-economic, behavioral, and farm characteristics. These characteristics include age, gender, education, level of off-farm income, farm size, proportion of remnant native vegetation on-farm, and ecological value of native vegetation on-farm. A sample of landholders who own greater than 2 ha of land in the South Australian Murray-Darling Basin region were sent a mail-based survey about their values and preferences for environmental management (N = 659, 52% response). Cross-tabulations and ANOVA statistical analysis techniques were used to compare the socio-economic attributes across three landholder classes: disengaged, moderately engaged, and highly engaged in native vegetation planting. Results indicate that highly engaged landholders were more likely to be female, formally educated, hobby farmers who managed small parcels of land and have high off-farm incomes, whereas disengaged landholders held significantly stronger farming connections (more farming experience, family have lived on the farm for more generations). Spatial analysis revealed area-specific differences in conservation opportunity and conservation priority. In some areas, properties of high ecological value were managed by highly engaged landholders, but nearby properties of high value were managed by moderately engaged or disengaged landholders. Environmental managers therefore cannot assume areas of high conservation priority will be areas of high conservation opportunity. At the regional scale, the potential for revegetation seems most promising within the moderately engaged landholder group considering the vast amount of land managed by this group in areas of high ecological value, particularly within the less represented Mallee and Coorong and Rangelands sub-regions. We suggest that incentive schemes which purchase conservation need to be targeted at disengaged landholders; mentoring schemes led by commercial farmers highly engaged in native vegetation planting should be directed at moderately engaged landholders, and; awards programs which acknowledge conservation successes should be targeted at highly engaged landholders.     

Modelling forest management within a global vegetation model—Part 2: Model validation from a tree to a continental scale

The construction of a new forest management module (FMM) within the ORCHIDEE global vegetation model (GVM) allows a realistic simulation of biomass changes during the life cycle of a forest, which makes many biomass datasets suitable as validation data for the coupled ORCHIDEE-FM GVM. This study uses three datasets to validate ORCHIDEE-FM at different temporal and spatial scales: permanent monitoring plots, yield tables, and the French national inventory data. The last dataset has sufficient geospatial coverage to allow a novel type of validation: inventory plots can be used to produce continuous maps that can be compared to continuous simulations for regional trends in standing volumes and volume increments. ORCHIDEE-FM performs better than simple statistical models for stand-level variables, which include tree density, basal area, standing volume, average circumference and height, when management intensity and initial conditions are known: model efficiency is improved by an average of 0.11, and its average bias does not exceed 25%. The performance of the model is less satisfying for tree-level variables, including extreme circumferences, tree circumference distribution and competition indices, or when management and initial conditions are unknown. At the regional level, when climate forcing is accurate for precipitation, ORCHIDEE-FM is able to reproduce most productivity patterns in France, such as the local lows of needleleaves in the Parisian basin and of broadleaves in south-central France. The simulation of water stress effects on biomass in the Mediterranean region, however, remains problematic, as does the simulation of the wood increment for coniferous trees. These pitfalls pertain to the general ORCHIDEE model rather than to the FMM. Overall, with an average bias seldom exceeding 40%, the performance of ORCHIDEE-FM is deemed reliable to use it as a new modelling tool in the study of the effects of interactions between forest management and climate on biomass stocks of forests across a range of scales from plot to country.     

浅议郴州市废弃矿山生态恢复途径

郴州市矿产资源丰富,采矿业发达,矿山资源开发导致了环境污染、生态破坏等一系列问题,矿山废弃地的生态恢复及景观重建已成为郴州市经济和社会发展需要迫切解决的问题之一.概括地介绍了郴州市的基本状况,分析了郴州市采矿业的无序发展对生态环境的影响,并针对矿山废弃地环境的污染问题,探索性地提出了郴州市废弃矿山生态恢复的途径.     

长白山的台风灾区范围及植被恢复动态——基于遥感技术的研究

通过对1985年和1987年Thematic Mapper(TM)影像中提取出的归一化植被指数进行对比分析,提取了1986年长白山自然保护区内遭受台风袭击后的灾区范围,并通过比较1988年和2007年的TM影像,分析了风灾区的植被恢复过程。同时,结合该地区的地形、水文、土壤和公路数据对风灾区的植被恢复进行了驱动力分析。发现地形驱动因子与风灾区的恢复程度呈高度相关,随着高程、坡度和平地所占比例的减少,恢复程度逐渐变好;此外水文、土壤和人类活动都对风灾区的植被恢复产生一定影响,另外人工干预恢复对植被生长也起着积极的作用。研究结果可供风灾区内植被的进一步恢复和森林防火工作参考。     

西南高山峡谷区植被变化及影响因素分析

西南高山峡谷区是我国典型生态脆弱区,认识其植被变化特征及影响因素可以为西南高山峡谷区生态环境建设对策的制定提供理论依据,对实现区域经济、环境以及生态和谐统一发展,具有一定的现实意义.基于2000~2019年NDVI、社会经济因子和自然因子数据集,采用一元线性回归法、Hurst指数、地理探测器模型和变异系数等方法分析了西南高山峡谷区NDVI时空变化及稳定性特征,并探讨了NDVI空间分异影响因素.结果表明：①空间上看,植被呈现东南高,西北低的分布格局,中高和高植被覆盖的区域面积占比71.71%,植被覆盖总体处于较高水平.时间上看,植被呈现改善趋势的区域面积占比85.90%,恢复效果明显,且未来植被变化趋势还将以改善为主.②高程、植被类型和土壤类型是影响NDVI空间分异的主导因子,q值均不低于0.40;气温和降雨量为次要因子,q值分别为0.274和0.225.双因子交互作用增强了单因子的影响力,表现为双因子增强和非线性增强两种关系,其中高程∩植被类型组合q值最高为0.714,其次是高程∩土壤类型组合q值为0.688.③研究时段内NDVI整体稳定性较好,低波动变化和较低波动变化的区域面积占比为89.95%;而中等以上波动的区域面积占比为10.05%,集中在海拔高、气温低、降雨少、土壤贫瘠和植被较差等生态环境相对脆弱的区域.植被变化是多因素综合作用的结果,需因地制宜,有针对性地采取不同策略修复西南高山峡谷区生态环境.     

水蚀环境植被恢复对土壤有机碳固存和团聚体稳定的影响：Meta分析

为明确水蚀环境不同条件下植被恢复策略对土壤固碳和团聚体稳定性的影响差异,通过搜集91篇论文的实验数据,以农田(或裸地)为对照,基于Meta分析评估土壤有机碳(SOC)储量和团聚体稳定性对水蚀环境退耕还林/还草措施的响应.结果表明：(1)退耕还林/还草均有利于提高SOC储量,改善土壤团聚体稳定性,但两者的优势功能存在差异,还林的固碳效应强于还草,而还草对增强团聚体稳定性的作用更强.(2)多因素Meta分析表明显著影响SOC的因素有：恢复年份、土壤黏粒含量、植被覆盖度、年平均降雨(MAP)、年平均气温(MAT)和土壤深度.其中植被恢复对SOC储量的正向效应随着植被覆盖率增加而提高;草地恢复在土壤黏粒含量为20%～32%下对SOC储量的提高效应更显著,在MAP>800 mm或MAT<15℃条件下更易促进草地固碳效应,不同恢复年限下的草地固碳效应无显著变化;而林地恢复在土壤黏粒含量>32%下对SOC储量的提高效应更显著,气候条件对林地SOC储量无限制性影响,林地恢复下的SOC储量与恢复年限间存在正向效应.(3)植被恢复在黏粒含量为20%～32%时对平均重量直径(MWD)和平均...